This is going to be a short one given yesterday's massive link dump and me being a bit busy to read much more.
On to the links!
The image above is my Azerothian alter-ego, the Nightelf Archdruid Adenadar on his favorite flying mount, the Veridian Netherdrake, which he unlocked over a decade ago. In the Good Old Days (i.e. before the "Warlords of Draenor" expansion), when you hit the level cap, you paid a nice person a good amount of gold and you were off and flying. Since Draenor, the Azerothian deities decided that was too easy and set up long quest chains and grinds to liberate oneself from the Azerothian soil. The link above describes the process.
After literal weeks of grinding, I finally achieved my goal and am now zooming around the Broken Isles on my classic mount. This is pretty much the end of everything I was working for in the new expansion, but I still need to go back to "Draenor" and unlock flying there, given that I bailed on that 3 years ago the last time I quit WoW.
I'm going to take a mini-WoW vacation for a couple of weeks and get back to unlocking Draenor flying when I get back. Should be a good deal easier now that I'm pretty well overpowered by spending time in the "Legion" expansion.
And after that, we get a new expansion in August!
Tech’s Two Philosophies (Stratechery)
I've dropped this link on a few folks as a nice illustration of the difference between the "augmentation" (build tools that make us more capable humans) and the "automation" positions (build tools that replace humans altogether) on technology. This article is an interesting application of that conflict as applied to contemporary technology companies' business models.
This is an interesting interview where the creator of Bayesian Networks takes the current Machine Learning field to task for focusing far too much on optimizing algorithms that optimize for problems that map onto "curve fitting" solutions while neglecting other classes of challenges that that allow the field to move on from correlational onto more powerful causal perspectives. Makes me wonder if this will rekindle interest in expert systems in the same way novel mathematical techniques allowed neural networks (now called "Deep Learners") to return to prominence after some time in the machine learning desert.
The Scientific Paper Is Obsolete (The Atlantic)
A solid look at how current scientific discourse is limited by a form factor that arose out of the early Enlightenment era, the scientific paper. It goes into an interesting history of Stephen Wolfram and his proprietary solution to the problem (Mathematica) and follows the absolutely stellar work going on in the Python community under the benevolent leadership of Fernando Pérez and his Jupyter (nee IPython) project. It's too bad that my career as a first author of papers is about a decade behind me, I would have adopted and promoted this tool with gusto. (Perhaps when I get back to having some mental space for such endeavors, I can use this as a way for publishing relevant work generated with my Passive Data Kit framework...)
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